Climate warming is threatening biodiversity by increasing temperatures beyond the optima of many ectotherms. Due to the inherent non-linear relationship between temperature and the rate of cellular processes, such shifts towards hot temperature are predicted to impose stronger selection compared to corresponding shifts toward cold temperature. This suggests that when adaptation to warming occurs, it should be relatively rapid and predictable. Here, we tested this hypothesis from the level of single-nucleotide polymorphisms to life-history traits, by conducting an evolve-and-resequence experiment on three genetic backgrounds of the beetle, Callosobruchus maculatus. Indeed, phenotypic evolution was faster and more repeatable at hot, relative to cold, temperature. However, at the genomic level, adaptation to heat was less repeatable when compared across genetic backgrounds. As a result, genomic predictions of phenotypic adaptation in populations exposed to hot temperature were accurate within, but not between, backgrounds. These results seem best explained by genetic redundancy and an increased importance of epistasis during adaptation to heat, and imply that the same mechanisms that exerts strong selection and increase repeatability of phenotypic evolution at hot temperature, reduce repeatability at the genome level. Thus, predictions of adaptation in key phenotypes from genomic data may become increasingly difficult as climate warms. This work has been nearly completed and is under review in Nature Ecology and Evolution. We will, however, also be adding in data from 6 additional beetle lines which act as “generalists”, switching between hot and cold temperatures every generation. We will run a similar pipeline and analyses for these lines, with the goal of improving our understanding of allele frequency dynamics during responses to climate warming from standing genetic variation and the role of epistasis and starting allele frequencies in governing these dynamics. These “switching” lines will also enable us to identify and quantify the evolution of phenotypic plasticity in response to variations in climate.